AI AGENTS
HuggingFace License-Drift Watcher to GitLab Compliance MR
Polls a pinned list of HuggingFace models on a schedule, detects when a model's license changes from the value your team approved.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires
- ActionFetch model-card metadata for each pinned modelHugging Face
- LogicCompare license vs. approved value; keep only changed
- ActionDraft MR body summarizing old vs. new license
- OutputOpen GitLab compliance MR with reviewers assignedGitLab
What it does
Watches the models your application pins (by repo id and revision) and catches the most dangerous silent change: a license switch. When a model relicenses from, say, Apache-2.0 to a restrictive custom license, this agent opens a GitLab MR against your compliance repo so the change is reviewed before it ships, not after.
When to use it
Use it when production code depends on specific HuggingFace models and your legal or security team must sign off on any license that touches the codebase. Ideal for teams that maintain an approved-licenses allowlist and treat unreviewed relicensing as a release blocker.
How it works
- 1A daily schedule fires the watcher.
- 2For each pinned model, fetch its current model-card metadata from HuggingFace, including the declared license.
- 3Compare each license against the last-approved value stored in your manifest; filter to only models whose license actually changed.
- 4If any drifted, draft an MR description summarizing old vs. new license per model.
- 5Open a GitLab merge request updating the manifest, labeled `compliance-review`, with reviewers auto-assigned.
Set it up
What you configure once, before turning it on.
- 1Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 2Connect GitLabRepos, MRs, pipelines, registry.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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